Mission-Based Design and Retrofit for Energy/Propulsion Systems of Solar-Powered UAVs: Integrating Propeller Slipstream Effects

Over twenty Solar-Powered Unmanned Aerial Vehicle (SPUAV) designs exist worldwide, yet few have successfully achieved uninterrupted high-altitude flight. This shortfall is attributed to several factors that cause the actual performance of SPUAV to fall short of expectations. Existing studies identify the propeller slipstream as one of these adverse factors, which leads to a decrease in the lift-drag ratio and an increase in energy consumption. However, traditional design methods for SPUAVs tend to ignore the potential adverse effects of slipstream at the top-level design phase. We find that this oversight results in a reduction in the feasible mission region of SPUAVs from 109 days to only 46 days. To address this issue, this paper presents a high-fidelity multidisciplinary design framework for the energy/propulsion systems of SPUAVs that integrates the effects of a propeller slipstream. Specifically, deep neural networks are employed to predict the lift-drag characteristics of SPUAVs under various slipstream conditions, and the energy performance is further analyzed by evaluating the time-varying state parameters throughout a day. Subsequently, the optimal solutions for the energy/propulsion systems specific to certain latitudes and dates are obtained through optimization design. The effectiveness of the proposed design framework was demonstrated on a 30-m wingspan SPUAV. The results indicated that, compared to the traditional design method, the proposed approach led to designs that more effectively accomplished closed-loop flight in designated regions and prevented the reduction of the feasible mission region. Additionally, through the targeted retrofit of the energy/propulsion systems, SPUAVs exhibited enhanced adaptability to the solar radiation characteristics of different mission points, resulting in a further expansion of the feasible mission region. Furthermore, this research also explored the variation trends in optimal solutions across different latitudes and dates and investigated the reasons and physical mechanisms behind these variations.